LibreAI / Agents IA / Tongyi Deep Research
// agents · Alibaba-NLP/DeepResearch

Tongyi Deep Research

Tongyi Deep Research est un projet de agents IA open source, créé par Alibaba-NLP (Alibaba-NLP/DeepResearch sur GitHub). Il compte 20 022 étoiles sur GitHub et 1 532 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 27 février 2026.

Tongyi Deep Research - Alibaba's open-source deep research agent and 30B model

★ 20,0 k étoiles⑂ 1,5 k forksApache-2.0mis à jour févr. 2026
▦ visuel — le README de ce projet ne contient aucune capture intégrable,
voici donc un emplacement réservé. Le guide ci-dessous est complet malgré tout.
// détails du projet

Détails du projet

Étoiles GitHub
20 022
Forks
1 532
Licence
Apache-2.0
Dernière mise à jour sur GitHub
27 février 2026
Catégorie
Agents IA
Type de fiche
Guide d'installation complet
Site officiel
Official site
// fonctionnement

Comment ça marche

  1. Prepare your questions

    Collect the research questions you want to evaluate, in the JSONL format the repo expects.

  2. Get the model and code

    Clone the repo and download the Tongyi-DeepResearch model weights from the Model Download section.

  3. Set up the environment

    Create the conda environment, install requirements, and copy the example environment file.

  4. Run your first research task

    Configure the inference script (model path, dataset, output) and run it.

// fonctionnalités

Pourquoi on l'adore

Deep research agent

A ReAct-style agent that plans, searches and synthesizes long-form research answers.

Open model weights

Tongyi-DeepResearch-30B-A3B weights are downloadable for local inference.

Tool use

Supports tools such as retrieval, web search and a calculator, configured per run in the inference script.

Document processing

Handles file references in questions, with documented formats and organization.

Benchmark suite

Includes the deep research benchmark evaluation used by the project.

Hosted option via OpenRouter

The model is available on OpenRouter, so you can run inference with no GPUs at all.

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// lancez-le

Lancez-le vous-même

  1. Clone the repository

    Get the source code from GitHub and enter the project directory.

    git clone https://github.com/Alibaba-NLP/DeepResearch.git
    cd DeepResearch
  2. Set up the environment

    The README's example uses conda with Python 3.10, then installs the requirements.

    conda create -n react_infer_env python=3.10.0
    conda activate react_infer_env
    pip install -r requirements.txt
  3. Configure and run inference

    Edit run_react_infer.sh (MODEL_PATH, DATASET, OUTPUT_PATH and any tool API keys), then run it.

    # Edit run_react_infer.sh per README step 4, then run the script - see README step 5
// cas d'usage

Ce que vous pouvez créer

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// faq

Questions fréquentes

Who maintains this project?

It is maintained by Alibaba's Tongyi team (Alibaba-NLP) on GitHub.

Is it free to use?

Yes - the project is Apache-2.0 licensed; model weights are provided under the terms on their download pages.

Does it need a paid API key?

Local runs need no API key beyond any tool credentials you enable (for example a search API). The OpenRouter route requires an OpenRouter account and is pay-per-use.

How does it compare to alternatives?

Compared with hosted deep-research features in chatbots, Tongyi Deep Research gives you the open model and agent code to run, inspect and benchmark yourself.

How do I get started?

Clone the repo, create the conda env, install requirements, download the weights, configure run_react_infer.sh and run your first question file.

// continuez l'exploration

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